Overview

Dataset statistics

Number of variables12
Number of observations2774
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory281.7 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_days_orders is highly overall correlated with frequencyHigh correlation
avg_products_order is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
avg_ticket is highly overall correlated with avg_products_orderHigh correlation
frequency is highly overall correlated with avg_days_ordersHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
orders is highly overall correlated with gross_revenue and 2 other fieldsHigh correlation
total_items is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
total_products is highly overall correlated with avg_products_order and 3 other fieldsHigh correlation
avg_ticket is highly skewed (γ1 = 51.90076808)Skewed
frequency is highly skewed (γ1 = 47.41381733)Skewed
items_returned is highly skewed (γ1 = 50.10197766)Skewed
avg_basket_size is highly skewed (γ1 = 44.87225707)Skewed
customer_id has unique valuesUnique
recency_days has 34 (1.2%) zerosZeros
items_returned has 1481 (53.4%) zerosZeros

Reproduction

Analysis started2024-05-22 11:08:59.515162
Analysis finished2024-05-22 11:09:13.535792
Duration14.02 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

UNIQUE 

Distinct2774
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15285.7
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:13.631726image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12626.65
Q113815.25
median15242.5
Q316779.75
95-th percentile17950.35
Maximum18287
Range5940
Interquartile range (IQR)2964.5

Descriptive statistics

Standard deviation1714.9849
Coefficient of variation (CV)0.11219538
Kurtosis-1.2069151
Mean15285.7
Median Absolute Deviation (MAD)1483.5
Skewness0.015990788
Sum42402531
Variance2941173.2
MonotonicityNot monotonic
2024-05-22T08:09:13.752022image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15060 1
 
< 0.1%
17850 1
 
< 0.1%
13047 1
 
< 0.1%
12583 1
 
< 0.1%
13748 1
 
< 0.1%
15100 1
 
< 0.1%
15291 1
 
< 0.1%
14688 1
 
< 0.1%
17809 1
 
< 0.1%
15311 1
 
< 0.1%
Other values (2764) 2764
99.6%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18265 1
< 0.1%
18263 1
< 0.1%
18261 1
< 0.1%
18260 1
< 0.1%

gross_revenue
Real number (ℝ)

HIGH CORRELATION 

Distinct2760
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2904.6492
Minimum36.56
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:13.866937image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum36.56
5-th percentile264.557
Q1628.195
median1170.87
Q32423.86
95-th percentile7579.4915
Maximum279138.02
Range279101.46
Interquartile range (IQR)1795.665

Descriptive statistics

Standard deviation10927.083
Coefficient of variation (CV)3.7619287
Kurtosis331.96378
Mean2904.6492
Median Absolute Deviation (MAD)690.475
Skewness16.261241
Sum8057496.7
Variance1.1940114 × 108
MonotonicityNot monotonic
2024-05-22T08:09:13.972433image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
178.96 2
 
0.1%
331 2
 
0.1%
2053.02 2
 
0.1%
745.06 2
 
0.1%
889.93 2
 
0.1%
734.94 2
 
0.1%
1314.45 2
 
0.1%
598.2 2
 
0.1%
731.9 2
 
0.1%
379.65 2
 
0.1%
Other values (2750) 2754
99.3%
ValueCountFrequency (%)
36.56 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
70.02 1
< 0.1%
77.4 1
< 0.1%
84.65 1
< 0.1%
90.3 1
< 0.1%
93.35 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
140438.72 1
< 0.1%
124564.53 1
< 0.1%
117375.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency_days
Real number (ℝ)

ZEROS 

Distinct252
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.627974
Minimum0
Maximum372
Zeros34
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:14.090879image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q110
median29
Q373
95-th percentile211
Maximum372
Range372
Interquartile range (IQR)63

Descriptive statistics

Standard deviation68.419023
Coefficient of variation (CV)1.2082195
Kurtosis3.4321191
Mean56.627974
Median Absolute Deviation (MAD)23.5
Skewness1.8983643
Sum157086
Variance4681.1627
MonotonicityNot monotonic
2024-05-22T08:09:14.217873image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.6%
4 87
 
3.1%
3 85
 
3.1%
2 85
 
3.1%
8 76
 
2.7%
10 67
 
2.4%
9 66
 
2.4%
7 65
 
2.3%
17 62
 
2.2%
22 55
 
2.0%
Other values (242) 2027
73.1%
ValueCountFrequency (%)
0 34
 
1.2%
1 99
3.6%
2 85
3.1%
3 85
3.1%
4 87
3.1%
5 43
1.6%
7 65
2.3%
8 76
2.7%
9 66
2.4%
10 67
2.4%
ValueCountFrequency (%)
372 1
 
< 0.1%
366 1
 
< 0.1%
360 1
 
< 0.1%
358 3
0.1%
354 1
 
< 0.1%
337 1
 
< 0.1%
336 2
0.1%
334 1
 
< 0.1%
333 2
0.1%
330 1
 
< 0.1%

orders
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0529921
Minimum2
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:14.332799image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median4
Q36
95-th percentile17
Maximum206
Range204
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.071603
Coefficient of variation (CV)1.4986973
Kurtosis183.94516
Mean6.0529921
Median Absolute Deviation (MAD)2
Skewness10.624664
Sum16791
Variance82.293981
MonotonicityNot monotonic
2024-05-22T08:09:14.449509image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 781
28.2%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
Other values (45) 278
 
10.0%
ValueCountFrequency (%)
2 781
28.2%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

total_items
Real number (ℝ)

HIGH CORRELATION 

Distinct1632
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1697.8205
Minimum2
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:14.565980image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile119
Q1330.25
median699.5
Q31478
95-th percentile4645.5
Maximum196844
Range196842
Interquartile range (IQR)1147.75

Descriptive statistics

Standard deviation6074.4301
Coefficient of variation (CV)3.5777812
Kurtosis438.72722
Mean1697.8205
Median Absolute Deviation (MAD)449
Skewness17.339197
Sum4709754
Variance36898701
MonotonicityNot monotonic
2024-05-22T08:09:14.713505image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
246 8
 
0.3%
150 8
 
0.3%
516 7
 
0.3%
394 7
 
0.3%
200 7
 
0.3%
1200 7
 
0.3%
272 7
 
0.3%
300 7
 
0.3%
219 7
 
0.3%
Other values (1622) 2698
97.3%
ValueCountFrequency (%)
2 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
25 1
< 0.1%
27 2
0.1%
30 1
< 0.1%
32 1
< 0.1%
33 2
0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
80997 1
< 0.1%
79963 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
62812 1
< 0.1%
58243 1
< 0.1%
57785 1
< 0.1%

total_products
Real number (ℝ)

HIGH CORRELATION 

Distinct468
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.72314
Minimum2
Maximum7837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:14.829565image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10
Q134
median72
Q3143
95-th percentile400.05
Maximum7837
Range7835
Interquartile range (IQR)109

Descriptive statistics

Standard deviation277.72934
Coefficient of variation (CV)2.140939
Kurtosis336.80085
Mean129.72314
Median Absolute Deviation (MAD)45
Skewness15.347204
Sum359852
Variance77133.584
MonotonicityNot monotonic
2024-05-22T08:09:14.959063image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 40
 
1.4%
35 34
 
1.2%
26 30
 
1.1%
27 30
 
1.1%
29 28
 
1.0%
33 27
 
1.0%
31 27
 
1.0%
15 27
 
1.0%
20 26
 
0.9%
42 26
 
0.9%
Other values (458) 2479
89.4%
ValueCountFrequency (%)
2 11
0.4%
3 13
0.5%
4 16
0.6%
5 16
0.6%
6 24
0.9%
7 14
0.5%
8 13
0.5%
9 20
0.7%
10 18
0.6%
11 23
0.8%
ValueCountFrequency (%)
7837 1
< 0.1%
5670 1
< 0.1%
5095 1
< 0.1%
4577 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1636 1
< 0.1%

avg_ticket
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1919
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.339156
Minimum2.15
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:15.079618image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum2.15
5-th percentile4.85
Q112.43
median17.945
Q325.075
95-th percentile88.4275
Maximum56157.5
Range56155.35
Interquartile range (IQR)12.645

Descriptive statistics

Standard deviation1071.0491
Coefficient of variation (CV)20.46363
Kurtosis2718.3215
Mean52.339156
Median Absolute Deviation (MAD)6.335
Skewness51.900768
Sum145188.82
Variance1147146.2
MonotonicityNot monotonic
2024-05-22T08:09:15.184147image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.49 7
 
0.3%
19.06 6
 
0.2%
16.82 6
 
0.2%
17.66 6
 
0.2%
16.92 5
 
0.2%
10 5
 
0.2%
17.13 5
 
0.2%
17.81 5
 
0.2%
19.44 5
 
0.2%
17.71 5
 
0.2%
Other values (1909) 2719
98.0%
ValueCountFrequency (%)
2.15 1
< 0.1%
2.43 1
< 0.1%
2.46 1
< 0.1%
2.51 1
< 0.1%
2.52 1
< 0.1%
2.65 1
< 0.1%
2.66 1
< 0.1%
2.71 1
< 0.1%
2.76 1
< 0.1%
2.77 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
1687.2 1
< 0.1%
952.99 1
< 0.1%
872.13 1
< 0.1%
841.02 1
< 0.1%
651.17 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%
615.75 1
< 0.1%

avg_days_orders
Real number (ℝ)

HIGH CORRELATION 

Distinct1155
Distinct (%)41.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.801889
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:15.289230image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q134.241667
median59
Q399
95-th percentile224
Maximum366
Range365
Interquartile range (IQR)64.758333

Descriptive statistics

Standard deviation66.515011
Coefficient of variation (CV)0.84407889
Kurtosis3.6744362
Mean78.801889
Median Absolute Deviation (MAD)30
Skewness1.8283611
Sum218596.44
Variance4424.2467
MonotonicityNot monotonic
2024-05-22T08:09:15.397552image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 21
 
0.8%
46 18
 
0.6%
55 17
 
0.6%
91 16
 
0.6%
31 16
 
0.6%
49 16
 
0.6%
42 15
 
0.5%
35 15
 
0.5%
21 15
 
0.5%
14 14
 
0.5%
Other values (1145) 2611
94.1%
ValueCountFrequency (%)
1 9
0.3%
2 4
0.1%
2.861538462 1
 
< 0.1%
3 6
0.2%
3.330357143 1
 
< 0.1%
3.351351351 1
 
< 0.1%
4 5
0.2%
4.191011236 1
 
< 0.1%
4.275862069 1
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
364 1
 
< 0.1%
363 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1228
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.061816117
Minimum0.0054644809
Maximum34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:15.507280image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.0054644809
5-th percentile0.0087719298
Q10.015873016
median0.024516482
Q30.042135511
95-th percentile0.11795995
Maximum34
Range33.994536
Interquartile range (IQR)0.026262495

Descriptive statistics

Standard deviation0.66943924
Coefficient of variation (CV)10.829526
Kurtosis2387.1027
Mean0.061816117
Median Absolute Deviation (MAD)0.010780219
Skewness47.413817
Sum171.47791
Variance0.4481489
MonotonicityNot monotonic
2024-05-22T08:09:15.629568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.07142857143 16
 
0.6%
0.04761904762 15
 
0.5%
0.01587301587 14
 
0.5%
0.0303030303 14
 
0.5%
0.02857142857 14
 
0.5%
0.02380952381 13
 
0.5%
0.06451612903 13
 
0.5%
0.1428571429 13
 
0.5%
0.025 12
 
0.4%
0.1176470588 12
 
0.4%
Other values (1218) 2638
95.1%
ValueCountFrequency (%)
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005602240896 2
0.1%
0.005617977528 1
 
< 0.1%
0.005633802817 2
0.1%
0.005681818182 1
 
< 0.1%
0.005698005698 2
0.1%
0.005714285714 3
0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
2 6
0.2%
1.5 1
 
< 0.1%
1.333333333 2
 
0.1%
1 4
0.1%
0.6666666667 3
0.1%
0.5522788204 1
 
< 0.1%
0.5349462366 1
 
< 0.1%

items_returned
Real number (ℝ)

SKEWED  ZEROS 

Distinct205
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.158976
Minimum0
Maximum80995
Zeros1481
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:15.767314image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile98
Maximum80995
Range80995
Interquartile range (IQR)9

Descriptive statistics

Standard deviation1564.3935
Coefficient of variation (CV)24.383081
Kurtosis2586.2541
Mean64.158976
Median Absolute Deviation (MAD)0
Skewness50.101978
Sum177977
Variance2447327.1
MonotonicityNot monotonic
2024-05-22T08:09:15.884065image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
6 63
 
2.3%
5 55
 
2.0%
12 45
 
1.6%
8 39
 
1.4%
7 38
 
1.4%
Other values (195) 653
23.5%
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
5 55
 
2.0%
6 63
 
2.3%
7 38
 
1.4%
8 39
 
1.4%
9 38
 
1.4%
ValueCountFrequency (%)
80995 1
< 0.1%
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%

avg_basket_size
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1932
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean245.46514
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:16.024611image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45
Q1103.33333
median172
Q3278.17381
95-th percentile585.55
Maximum40498.5
Range40497.5
Interquartile range (IQR)174.84048

Descriptive statistics

Standard deviation808.02308
Coefficient of variation (CV)3.2918039
Kurtosis2224.0987
Mean245.46514
Median Absolute Deviation (MAD)81
Skewness44.872257
Sum680920.29
Variance652901.3
MonotonicityNot monotonic
2024-05-22T08:09:16.140568image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
86 9
 
0.3%
60 8
 
0.3%
75 8
 
0.3%
73 7
 
0.3%
136 7
 
0.3%
208 7
 
0.3%
197 7
 
0.3%
82 7
 
0.3%
105 7
 
0.3%
Other values (1922) 2696
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
11.875 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%
2000 1
< 0.1%
1903.5 1
< 0.1%

avg_products_order
Real number (ℝ)

HIGH CORRELATION 

Distinct1003
Distinct (%)36.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.122355
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2024-05-22T08:09:16.252954image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.5
Q110.127083
median17.296703
Q328.083333
95-th percentile56.64697
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.95625

Descriptive statistics

Standard deviation18.868378
Coefficient of variation (CV)0.85290999
Kurtosis24.16784
Mean22.122355
Median Absolute Deviation (MAD)8.2967033
Skewness3.1572707
Sum61367.414
Variance356.01568
MonotonicityNot monotonic
2024-05-22T08:09:16.374624image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 44
 
1.6%
14 31
 
1.1%
11 29
 
1.0%
9 26
 
0.9%
1 26
 
0.9%
10.5 25
 
0.9%
7.5 25
 
0.9%
17.5 25
 
0.9%
18 24
 
0.9%
9.5 24
 
0.9%
Other values (993) 2495
89.9%
ValueCountFrequency (%)
1 26
0.9%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 8
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 21
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
203.5 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%
114 1
< 0.1%
110.3333333 1
< 0.1%
109.6666667 2
0.1%

Interactions

2024-05-22T08:09:12.113448image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:08:59.739390image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.867345image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.895873image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.947379image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:04.157495image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:05.303693image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:06.415019image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:07.588248image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.679765image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.703370image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:10.826644image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.189942image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:08:59.815993image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.944978image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.979149image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:03.026735image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:04.239892image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:05.384877image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:06.492392image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:07.667375image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.759526image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.785109image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:10.908220image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.279944image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:08:59.892567image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.021374image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.060827image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:03.107680image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:04.321587image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:05.467245image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:06.571224image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:07.747801image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.837574image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.865000image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.000862image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.387119image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:08:59.975933image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.104864image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.145859image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-05-22T08:09:11.087744image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.497447image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.058930image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.201322image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.231412image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:03.291552image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-05-22T08:09:10.043246image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.176876image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.595476image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.144214image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-05-22T08:09:06.847559image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.039551image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-05-22T08:09:10.134829image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.281337image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.681921image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.230150image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.375158image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.407791image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:03.597776image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:04.723032image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:05.844653image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:06.932460image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.127150image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.178812image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:10.238998image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.382289image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.772380image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
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2024-05-22T08:09:02.487423image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:03.681223image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:04.828421image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:05.931065image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:07.019476image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.206400image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.257331image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:10.336054image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.461621image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.854817image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.392257image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.537002image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.571461image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:03.799177image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:04.913254image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:06.038245image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:07.100786image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.288301image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.352668image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:10.423467image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.578180image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:12.935836image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.605938image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.620556image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.669646image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:03.883931image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:05.022526image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:06.124254image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:07.180454image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.373114image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.433925image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:10.510537image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.663079image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:13.024884image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.690115image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.718231image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.756531image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:03.974232image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:05.111822image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:06.241691image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:07.423934image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.465330image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.534781image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:10.632375image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.752450image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:13.121728image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:00.787910image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:01.817410image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:02.868205image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:04.075576image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:05.213178image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:06.330973image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:07.508960image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:08.589427image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:09.623751image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:10.730353image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-05-22T08:09:11.839665image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Correlations

2024-05-22T08:09:16.468222image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
avg_basket_sizeavg_days_ordersavg_products_orderavg_ticketcustomer_idfrequencygross_revenueitems_returnedordersrecency_daystotal_itemstotal_products
avg_basket_size1.000-0.0420.4310.199-0.1200.0240.6020.2150.125-0.1040.7590.402
avg_days_orders-0.0421.0000.061-0.079-0.012-0.951-0.366-0.214-0.4770.223-0.342-0.301
avg_products_order0.4310.0611.000-0.6270.006-0.0700.2810.0260.017-0.1040.3110.721
avg_ticket0.199-0.079-0.6271.000-0.1410.0800.2740.1890.0900.0340.196-0.382
customer_id-0.120-0.0120.006-0.1411.0000.013-0.085-0.0580.0130.013-0.0780.012
frequency0.024-0.951-0.0700.0800.0131.0000.2540.1730.317-0.1240.2360.199
gross_revenue0.602-0.3660.2810.274-0.0850.2541.0000.4620.762-0.3740.9220.722
items_returned0.215-0.2140.0260.189-0.0580.1730.4621.0000.425-0.1870.4270.328
orders0.125-0.4770.0170.0900.0130.3170.7620.4251.000-0.4470.7030.659
recency_days-0.1040.223-0.1040.0340.013-0.124-0.374-0.187-0.4471.000-0.366-0.391
total_items0.759-0.3420.3110.196-0.0780.2360.9220.4270.703-0.3661.0000.707
total_products0.402-0.3010.721-0.3820.0120.1990.7220.3280.659-0.3910.7071.000

Missing values

2024-05-22T08:09:13.281358image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-22T08:09:13.455047image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysorderstotal_itemstotal_productsavg_ticketavg_days_ordersfrequencyitems_returnedavg_basket_sizeavg_products_order
0178505391.21372.034.01733.0297.018.151.00000034.00000040.050.9705888.735294
1130473232.5956.09.01390.0171.018.9052.8333330.02839135.0154.44444419.000000
2125836705.382.015.05028.0232.028.9026.5000000.04043150.0335.20000015.466667
313748948.2595.05.0439.028.033.8792.6666670.0179860.087.8000005.600000
415100876.00333.03.080.03.0292.0020.0000000.07500022.026.6666671.000000
5152914623.3025.014.02102.0102.045.3326.7692310.04023029.0150.1428577.285714
6146885630.877.021.03621.0327.017.2219.2631580.057377399.0172.42857115.571429
7178095411.9116.012.02057.061.088.7239.6666670.03361341.0171.4166675.083333
81531160767.900.091.038194.02379.025.544.1910110.243968474.0419.71428626.142857
9160982005.6387.07.0613.067.029.9347.6666670.0244760.087.5714299.571429
customer_idgross_revenuerecency_daysorderstotal_itemstotal_productsavg_ticketavg_days_ordersfrequencyitems_returnedavg_basket_sizeavg_products_order
561117290525.243.02.0404.0102.05.1513.00.1538460.0202.00000051.0
56201478577.4010.02.084.03.025.805.00.4000000.042.0000001.5
562117254272.444.02.0252.0112.02.4311.00.1818180.0126.00000056.0
563717232421.522.02.0203.036.011.7112.00.1666670.0101.50000018.0
563817468137.0010.02.0116.05.027.404.00.5000000.058.0000002.5
564913596697.045.02.0406.0166.04.207.00.2857140.0203.00000083.0
5655148931237.859.02.0799.073.016.962.01.0000000.0399.50000036.5
568014126706.137.03.0508.015.047.083.01.00000050.0169.3333335.0
5686135211092.391.03.0733.0435.02.514.50.3333330.0244.333333145.0
569615060301.848.04.0262.0120.02.521.04.0000000.065.50000030.0